Modeling public responses to soft-target transportation terror

Abstract

Transportation systems are one of the most frequent and high-profile targets for terrorist attacks, and such attacks can cause reduced or altered public travel behavior that can have severe economic consequences. Thus, understanding the relationship between transportation terror and public response is critical. We recruited n = 430 participants to read one of three hypothetical transportation-based terror attacks, and use Partial Least Squares path modeling to identify the interrelationships between the affective, cognitive, and (intended) behavioral facets of their reactions. The three terror scenarios were structured to allow for comparisons between a cyber and non-cyber attack on ground transportation, and an aviation versus ground explosives attack, which allowed us to test the robustness of the path model across situational features. Results indicated that the attack features did not moderate any of the interrelationships between reaction variables, but had medium-sized effects on self-reported risk perception. Collapsing data from all three scenarios into a single path model confirmed previously reported findings regarding the opposing roles of fear and anger in risk perception, suggested differing roles for terrorism risk attitudes and general risk attitudes, and found a surprisingly negligible role for self-reported trust in government. Implications for further research on soft-target and transportation-based terrorism risk perception are discussed.